Hongxu Yin | DeepAI

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Featured Co-authors

Jan Kautz
130 publications
Hai Li
81 publications
Daguang Xu
64 publications
Jose M. Alvarez
52 publications
Fei Sun
48 publications
Bichen Wu
39 publications
Holger R. Roth
39 publications
Wenqi Li
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Niraj K. Jha
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Arash Vahdat
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Pavlo Molchanov
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∙ 04/02/2023

Recurrence without Recurrence: Stable Video Landmark Detection with Deep Equilibrium Models

Cascaded computation, whereby predictions are recurrently refined over s...

0 Paul Micaelli, et al. ∙

∙ 10/13/2022

Structural Pruning via Latency-Saliency Knapsack

Structural pruning can simplify network architecture and improve inferen...

0 Maying Shen, et al. ∙

∙ 06/20/2022

Global Context Vision Transformers

We propose global context vision transformer (GC ViT), a novel architect...

0 Ali Hatamizadeh, et al. ∙

∙ 03/22/2022

GradViT: Gradient Inversion of Vision Transformers

In this work we demonstrate the vulnerability of vision transformers (Vi...

0 Ali Hatamizadeh, et al. ∙

∙ 02/14/2022

Do Gradient Inversion Attacks Make Federated Learning Unsafe?

Federated learning (FL) allows the collaborative training of AI models w...

0 Ali Hatamizadeh, et al. ∙

∙ 12/14/2021

AdaViT: Adaptive Tokens for Efficient Vision Transformer

We introduce AdaViT, a method that adaptively adjusts the inference cost...

0 Hongxu Yin, et al. ∙

∙ 10/22/2021

When to Prune? A Policy towards Early Structural Pruning

Pruning enables appealing reductions in network memory footprint and tim...

0 Maying Shen, et al. ∙

∙ 10/20/2021

HALP: Hardware-Aware Latency Pruning

Structural pruning can simplify network architecture and improve inferen...

0 Maying Shen, et al. ∙

∙ 10/10/2021

NViT: Vision Transformer Compression and Parameter Redistribution

Transformers yield state-of-the-art results across many tasks. However, ...

0 Huanrui Yang, et al. ∙

∙ 07/13/2021

Deep Neural Networks are Surprisingly Reversible: A Baseline for Zero-Shot Inversion

Understanding the behavior and vulnerability of pre-trained deep neural ...

8 Xin Dong, et al. ∙

∙ 04/15/2021

See through Gradients: Image Batch Recovery via GradInversion

Training deep neural networks requires gradient estimation from data bat...

0 Hongxu Yin, et al. ∙

∙ 02/20/2021

MHDeep: Mental Health Disorder Detection System based on Body-Area and Deep Neural Networks

Mental health problems impact quality of life of millions of people arou...

0 Shayan Hassantabar, et al. ∙

∙ 07/29/2020

Fully Dynamic Inference with Deep Neural Networks

Modern deep neural networks are powerful and widely applicable models th...

0 Wenhan Xia, et al. ∙

∙ 04/18/2020

Efficient Synthesis of Compact Deep Neural Networks

Deep neural networks (DNNs) have been deployed in myriad machine learnin...

0 Wenhan Xia, et al. ∙

∙ 12/18/2019

Dreaming to Distill: Data-free Knowledge Transfer via DeepInversion

We introduce DeepInversion, a new method for synthesizing images from th...

27 Hongxu Yin, et al. ∙

∙ 10/11/2019

DiabDeep: Pervasive Diabetes Diagnosis based on Wearable Medical Sensors and Efficient Neural Networks

Diabetes impacts the quality of life of millions of people. However, dia...

13 Hongxu Yin, et al. ∙

∙ 05/27/2019

Incremental Learning Using a Grow-and-Prune Paradigm with Efficient Neural Networks

Deep neural networks (DNNs) have become a widely deployed model for nume...

0 Xiaoliang Dai, et al. ∙

∙ 01/30/2019

Hardware-Guided Symbiotic Training for Compact, Accurate, yet Execution-Efficient LSTM

Many long short-term memory (LSTM) applications need fast yet compact mo...

0 Hongxu Yin, et al. ∙

∙ 12/21/2018

ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation

This paper proposes an efficient neural network (NN) architecture design...

0 Xiaoliang Dai, et al. ∙

∙ 05/30/2018

Grow and Prune Compact, Fast, and Accurate LSTMs

Long short-term memory (LSTM) has been widely used for sequential data m...

0 Xiaoliang Dai, et al. ∙

∙ 05/30/2018

Grow and Prune Compact, Fast, and AccurateLSTMs

Long short-term memory (LSTM) has been widely used for sequential data m...

0 Xiaoliang Dai, et al. ∙

∙ 11/06/2017

NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm

Neural networks (NNs) have begun to have a pervasive impact on various a...

0 Xiaoliang Dai, et al. ∙